Differing six minute pacing strategies affect anaerobic contribution, oxygen uptake, muscle deoxygenation and cycle performance
Bibliographic record
Abstract
BACKGROUND: This study compared an all-out start (AO) to a constant power start strategy (CON) during a 6 min cycle performance on utilization of W´ (energy above critical power [CP]), muscle deoxygenation (HHb), oxygen uptake (VO2) and performance in recreationally active individuals. The AO strategy was similar to that employed by rowers. METHODS: Eight healthy males (age =24±3 y) completed a ramp test to fatigue (VO2peak =4.42±0.54 L∙min-1; peak power =385±35 W) and a 3-min all-out test to determine CP and the CON work rate. The AO strategy began with a 12 s sprint, followed by 258 s at 5%<CON. The CON work rate was calculated as CP*W +(W´J/360 s) and performed for the initial 270 s of the ride. Both groups increased their effort, in 30 s intervals, over the last 90 s of each trial. The last 30 s was a sprint. RESULTS: Total W´ utilized was higher during CON vs. AO (18,109±5439 J vs. 13,754±3543 J, P<0.05). The HHb/VO2 ratio reflected a duration mismatch between O2 provision to O2 utilization during CON compared to AO (118 s vs. 58 s, P<0.05). Mean work rate was higher in CON compared to AO (315±21 W vs. 302±64 W, P<0.05). CONCLUSIONS: CON yielded a greater utilization of W´ and a higher mean work rate compared to AO during a traditional rowing stratagem during a 6-min cycle performance in recreationally active individuals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".